Autonomous planting of broadleaf trees in sight

Autonomous planting machine with spruce forest behind. Photo.


Stina Johannesson

Autonomous forest planting has the potential to be both more cost-effective and more considerate of different ecosystem services compared to manual planting. In a research project within the competence centre Trees For Me researchers at Luleå University of Technology will find solutions to the challenges of autonomous forest planting technology and how it can be used when planting fast growing broadleaf trees.

”One can speculate that the manual work is moved from the machine which means that the same operator can probably generate a significantly greater value, for example by being responsible for clusters of machines, which means that the productivity will increase while the working environment will also be improved. However, manual measures such as programming, transport and maintenance will still need to be done manually”, says Magnus Karlberg, professor of machine design at Luleå University of Technology, who leads the research project.

Magnus Karlberg emphasizes that the quality of the seedling establishment will be better since the autonomous machines will be significantly more precise and flexible when choosing a planting point.

“With modern sensor technology, the machine will be able to identify objects and properties in the environment that humans don’t even perceive. This gives the opportunity to, for each individual plant, choose exactly where it should be planted to maximize, for example, the plant quality and survival”, says Magnus Karlberg.

He also highlights the advantages of the autonomous planting when soil scarification is needed, since a smaller volume of the soil than before would need to be processed and the environmental footprint thus can be minimized. The size of the carrier could be radically reduced and these lighter units would lower the carbon footprint.

Many challenges to solve

Magnus Karlberg emphasizes that both the hardware and software must be developed in order to, for example, contribute to optimal perception, crane control and drivability. The requirements are still unclear regarding which type of land should be used for the autonomous planting, whether seeds, containerized seedlings or cuttings are best suited for this planting, whether the planting should be done in strict rows or randomly and whether the soil should be fertilized or not. Other challenges are the legal aspects.

“It is unclear where the responsibility lies in case of accidents and damage and whether it is the owner of the machine, the one who ordered the autonomous job or the machine developer that is responsible”, says Magnus Karlberg.

Erik Arvidsson is a PhD student in the research project, at Luleå University of Technology, and will investigate what information and what decisions are needed for the autonomous systems to function and how the technology can be optimized based on the requirements.

“Autonomous machines are strictly dependent on sensors to function, but which ones? That’s a question I work on continuously”, says Erik Arvidsson.

Knowledge on fast growing broadleaves is missing

Both emphasize that the knowledge on autonomous regeneration of fast growing broadleaved trees is very limited. By focusing the research on planting on forest land rather than arable land the demands on the technology increase, as the aggregates must be trained to avoid more obstacles. And collaborations are important in the development.

“Before we decide on which plant material we will design the machine for, we have to discuss further with the centre’s researchers who focus on tree breeding and with nurseries in Sweden and Finland to know what the optimal plant looks like”, says Erik Arvidsson.

Long-term and unique

The internationally unique technology is developed from the ground up and is not based on existing harvester software, as some existing solutions. Magnus Karlberg emphasizes that the autonomous solution for planting will probably take a few decades to implement, but says that remote-controlled and then semi-autonomous technology will be available earlier. The market demand will also affect the implementation. And although it may take some time before the technology reaches the market, Magnus Karlberg believes that it will then be groundbreaking.

“We don't want to limit the machine to human ability but rather use the technology's full potential.”

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